A novel coupled FDM-DEM modelling method for flexible membrane boundary in laboratory tests

Difficulties are involved in discrete element method (DEM) modelling of the flexible boundary, that is, the membranes covering the soil sample, which can be commonly found in contemporary laboratory soil tests. In this paper, a novel method is proposed wherein the finite difference method (FDM) and DEM are coupled to simulate the rubber membrane and soil body, respectively. Numerical plane strain and triaxial tests, served by the flexible membrane, are implemented and analysed later. The effect of the membrane modulus on the measurement accuracy is considered, with analytical formulae derived to judge the significance of this effect. Based on an analysis of stress-strain responses and the grain rotation field, the mechanical performances produced by the flexible and rigid lateral boundaries are compared for the plane strain test. The results show that (1) the effect of the membrane on the test result becomes more significant at larger strain level because the membrane applies additional lateral confining pressure to the soil body; (2) the tested models reproduce typical stress and volumetric paths for specimens with shear bands; (3) for the plane strain test, the rigid lateral boundary derives a much higher peak strength and larger bulk dilatation, but a similar residual strength, compared with the flexible boundary. The latter produces a more uniform (or ‘diffuse') rotation field and more mobilised local kinematics than does the former. All simulations show that the proposed FDM-DEM coupling method is able to simulate laboratory tests with a flexible boundary membrane.     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

Directional interpolation infinite element for dynamic problems in saturated porous media

In this study, a directional interpolation infinite element suited to a saturated porous medium is presented to account for dynamic problems with semi-infi     

Discovery of Four New Clusters in the Cygnus Cloud

We report the discovery of four new open clusters(named QC 1,QC 2,QC 3 and QC 4)in the direction of Cygnus Cloud and select their members based on five astrometric parameters(l,b,ω,μα*,μδ)of Gaia DR2.We also derive their astrophysical parameters for each new cluster.Structure parameters are generated by fitting the radial density distribution with a King’s profile.Using solar metallicity,we performed isochrone-fitting on their purified color-magnitude diagrams(CMDs)to derive the age of the clusters.The known cluster NGC 7062 in an adjacent area is chosen to verify our identification process.The estimated distance,reddening and age of NGC 7062 are in good agreement with the literature.     

毛乌素沙区1961-2016年降水特征

基于毛乌素沙区10个气象站1961-2016年观测资料，应用Mann-Kendall方法和t检验法对各气象站年降水量进行了突变检验，借助小波分析讨论了各气象站年降水量的周期特征，根据降水量等值线划分结果对整个研究区分区分析了年、季、月和日尺度上的降水变化特征，并在两个时段上分析了季节性降水的差异。结果表明：毛乌素沙区年降水量空间特征差异明显，东部亚区呈上升趋势，中西部亚区呈下降趋势，但变化趋势不显著且无突变发生；降水年内分配不均，干湿季分明，降水集中在5-9月，夏秋季降水占全年降水比重大，季、月和日尺度降水量存在梯度递减变化；年降水量的年际变化过程存在多重时间尺度的自相似结构；近26年的冬春季降水增加显著，但降水波动幅度小于前30年。     

sPL震相在巴东M4.3地震序列震源深度测定中的应用

根据近震深度震相sPL的基本特征，对2017-06-16巴东M4.3地震序列震源深度进行分析，运用频率-波数（F-K）方法模拟不同深度下的理论地震图，并与实际波形拟合对比，得出震源深度分布。结果显示，该地震序列的震源深度集中在3~4 km范围内，误差约为1 km，表明在三峡地区利用sPL震相可以获得较为可靠的震源深度。     

Classification of stellar spectra with SVM based on within-class scatter and between-class scatter

Support Vector Machine (SVM) is a popular data mining technique, and it has been widely applied in astronomical tasks, especially in stellar spectra classification. Since SVM doesn’t take the data distribution into consideration, and therefore, its classification efficiencies can’t be greatly improved. Meanwhile, SVM ignores the internal information of the training dataset, such as the within-class structure and between-class structure. In view of this, we propose a new classification algorithm-SVM based on Within-Class Scatter and Between-Class Scatter (WBS-SVM) in this paper. WBS-SVM tries to find an optimal hyperplane to separate two classes. The difference is that it incorporates minimum within-class scatter and maximum between-class scatter in Linear Discriminant Analysis (LDA) into SVM. These two scatters represent the distributions of the training dataset, and the optimization of WBS-SVM ensures the samples in the same class are as close as possible and the samples in different classes are as far as possible. Experiments on the K-, F-, G-type stellar spectra from Sloan Digital Sky Survey (SDSS), Data Release 8 show that our proposed WBS-SVM can greatly improve the classification accuracies.     

新疆绿洲城镇组群内部经济联系及空间差异测度研究

绿洲城镇组群是新疆特殊区域形成的规模相对较小的单一中心空间自组织模式。运用城市中心性指数、城市经济联系模型和Theil系数对新疆八大绿洲城镇组群内部城镇中心性、经济联系及空间差异测度。结果显示：绿洲城镇组群内部的中心城市的中心性职能较强，周边城镇的中心性职能相对较弱，形成了单中心的空间自组织模式；绿洲城镇组群内部经济联系量和经济联系隶属度大小的排序一致，离中心城市的距离越近、经济发展水平越高，经济联系隶属度越高；近10 a年来绿洲城镇组群的整体空间差异一直在扩大，且呈现出继续扩大趋势。在此基础上，提出了建立区域合作协调机制、明确城镇组群发展方向、增强中心城市的辐射带动作用、实现产业合理分工以及构建制度保障体系促进绿洲城镇组群的协同发展。     

北京主城区伪基站时空规律分析

随着公众移动通信的快速发展,伪基站的泛滥不仅破坏正常电信秩序,危害公共安全,而且严重损害群众财产权益,侵犯公民个人隐私,已成为社会一大公害。如何从垃圾短信大数据中挖掘出伪基站活动的时空规律,寻找有效的防控方案,从源头上进行打击和治理成为管理部门和研究者共同关注的焦点。本文基于北京市垃圾短信数据,利用非负矩阵分解的方法分析伪基站的时空分布规律;并利用TF-IDF构建垃圾短信分类模型,对垃圾短信进行分类,结合土地利用数据,分析伪基站在发送不同类型垃圾短信时的时空分布规律。结果显示：北京市垃圾短信多分布于路网和中心城区;白天垃圾短信数量远远多于晚上;垃圾短信的分布随时间的推移沿着路网逐渐向内收缩;发送不同类型垃圾短信的伪基站的时空分布具有一定的差异;通过非负矩阵分解得到的结果,与垃圾短信分类后得到的结果有很好的匹配。研究表明,非负矩阵分解具有实现上的简便性、分解形式和分解结果上的可解释性等优点,可以有针对性的为有关部门建言打击伪基站的有效方案,对于伪基站违法行为的治理具有一定的意义。     

Permeability Characteristics of Broken Coal and Rock Under Cyclic Loading and Unloading

Natural Resources Research - During longwall mining, the permeability evaluation in a caving zone is one of the most challenging risks for mine operators because it controls the behavior of gas...